Motor control theorists have postulated that production of rapid, coordinated movements requires control circuitry that can bypass sensory feedback delays by providing an estimate of the consequences resulting from a motor command. This control element, termed a forward internal model, receives an efferent copy of the motor command and information about the current state in order to predict the future state of the limb (i.e., kinematic variables like position and velocity). Previous psychophysical, imaging, and patient case studies suggest that the cerebellum is a possible location for implementation of an internal model. However, few electrophysiological studies have investigated whether the firing discharge from cerebellar neurons is consistent with the properties of a forward internal model. The ultimate goal of this project is to evaluate whether the simple spike firing from Purkinje cells (PCs) in lobules IV-VI of the intermediate/lateral cerebellar zones is consistent with output from a forward internal model. Although no single result will conclusively prove this hypothesis, two electrophysiology experiments examining hand movements in rhesus macaques are proposed to test several aspects of a forward internal model. Aim 1 will examine whether PC firing predicts future hand kinematics in a task-independent manner. Aim 2 will further evaluate model adaptability and whether changing model inputs alters predicted kinematics. The results will either show that PC firing is incompatible with the output expected from a forward model or provide solid support for future experiments. PUBLIC HEALTH RELEVANCE: An increased knowledge of healthy cerebellar function is essential for understanding how cerebellar brain injury or disease might manifest clinically and lead to deficits in motor coordination, learning, and movement timing. Recording activity from Purkinje cells, a specific type of neuron in the cerebellar cortex, during movement learning tasks may lead to increased understanding of how these cells act as a network to encode movement variables and learn new motor tasks. Perhaps most importantly, insights regarding the control parameters required for coordinated movements may lead to more specific rehabilitation therapies for patients with movement disorders and improved algorithms for controlling smart prosthetics.